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Record W3044866625 · doi:10.3846/enviro.2020.675

Filtrates and sludge generated in the physicochemical treatment of wastewater from the lead-acid batteries production

2020· article· en· W3044866625 on OpenAlexaff
Terese Rauckyte-Żak, Beata Gorczyca, Sławomir Żak

Bibliographic record

VenueEnvironmental engineering · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsToxicity characteristic leaching procedureLimeLeaching (pedology)WastewaterChemistrySewage treatmentPulp and paper industryWaste managementEnvironmental chemistryMaterials scienceMetallurgyEnvironmental scienceHeavy metals

Abstract

fetched live from OpenAlex

Total lead (TPb) exists in Crude Wastewater (CW) from production of Lead-Acid Batteries (LABs) in water (WPb) and solid phase (SPb) as colloids and suspended solids. Sludges produced in chemical treatment of these wastewater were dewatered in Chamber Pressure Press (CPP). Samples of dewatered sludges (Ss) were analyzed with Toxicological Characteristic Leaching Procedure (TCLP) to determine concentration of Pb in the extract (Ex(TCLP)). Selected sludges were also analyzed using Tessier’s procedure for fractions. Concentration of lead in filtrates (Fs) as well as in the sludges were different, depending on the mechanisms involved in converting soluble lead to its less soluble forms. Sludges produced in chemical treatment with 10% NaOH and Lime Milk (LM), CaO or Ca(OH)2, followed by coagulation with (Ixonos Na3T ®) contained lowest concentration of lead. The TPb in filtrates below 0.4 mg/L at pH > 8.90±0.3, and Ex(TCLP) of less than 5.0 mg/L were obtained in this treatment. Potential recovery of lead from sludges have been investigated.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.474

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.182
Teacher spread0.169 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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